Development of Risk Stratification Predictive Models for Cervical Deformity Surgery.
Document Type
Article
Publication Date
12-1-2022
Publication Title
Neurosurgery
Keywords
washington; swedish; swedish neurosci; Humans; Adolescent; Thoracic Vertebrae; Kyphosis; Lordosis; Cervical Vertebrae; Risk Assessment; Retrospective Studies
Abstract
BACKGROUND: As corrective surgery for cervical deformity (CD) increases, so does the rate of complications and reoperations. To minimize suboptimal postoperative outcomes, it is important to develop a tool that allows for proper preoperative risk stratification.
OBJECTIVE: To develop a prognostic utility for identification of risk factors that lead to the development of major complications and unplanned reoperations.
METHODS: CD patients age 18 years or older were stratified into 2 groups based on the postoperative occurrence of a revision and/or major complication. Multivariable logistic regressions identified characteristics that were associated with revision or major complication. Decision tree analysis established cutoffs for predictive variables. Models predicting both outcomes were quantified using area under the curve (AUC) and receiver operating curve characteristics.
RESULTS: A total of 109 patients with CD were included in this study. By 1 year postoperatively, 26 patients experienced a major complication and 17 patients underwent a revision. Predictive modeling incorporating preoperative and surgical factors identified development of a revision to include upper instrumented vertebrae > C5, lowermost instrumented vertebrae > T7, number of unfused lordotic cervical vertebrae > 1, baseline T1 slope > 25.3°, and number of vertebral levels in maximal kyphosis > 12 (AUC: 0.82). For developing a major complication, a model included a current smoking history, osteoporosis, upper instrumented vertebrae inclination angle < 0° or > 40°, anterior diskectomies > 3, and a posterior Smith Peterson osteotomy (AUC: 0.81).
CONCLUSION: Revisions were predicted using a predominance of radiographic parameters while the occurrence of major complications relied on baseline bone health, radiographic, and surgical characteristics.
Clinical Institute
Neurosciences (Brain & Spine)
Clinical Institute
Orthopedics & Sports Medicine
Department
Neurosciences
Department
Orthopedics
Department
Surgery
Recommended Citation
Passias, Peter G; Ahmad, Waleed; Oh, Cheongeun; Imbo, Bailey; Naessig, Sara; Pierce, Katherine; Lafage, Virginie; Lafage, Renaud; Hamilton, D Kojo; Protopsaltis, Themistocles S; Klineberg, Eric O; Gum, Jeffrey; Schoenfeld, Andrew J; Line, Breton; Hart, Robert A; Burton, Douglas C; Bess, Shay; Schwab, Frank J; Smith, Justin S; Shaffrey, Christopher I; Ames, Christopher P; and International Spine Study Group, "Development of Risk Stratification Predictive Models for Cervical Deformity Surgery." (2022). Articles, Abstracts, and Reports. 6606.
https://digitalcommons.providence.org/publications/6606
